Pacific Symposium on Biocomputing
January 3-7, 2026
The Big Island of Hawaii, U.S.A.
Call for Papers and Posters
Precision Medicine:
Integrating large scale data and intermediate phenotypes for understanding health and treating disease
Motivation
Precision medicine draws on deep biological knowledge to tailor medical decisions and treatments to individual patients in a data-driven manner. For PSB 2026, we are particularly interested in papers that use advanced computational and methodological approaches for analysis of varied large scale data that characterize health and disease. This includes studies that integrate high-throughput biological data that span intermediate molecular and cellular phenotypes underlying disease, with application to precision medicine. We welcome papers whose results will promote our understanding of disease mechanisms and treatment based on innovative analysis of biological data.
Achieving the promise of precision medicine will require applying state-of-the-art computational tools to integrate and interpret the large volumes of data being generated. To this end, we invite submission of papers that analyze genomic, epigenomic, transcriptomic, proteomic, multi-omic, metabolomic, metagenomic, or other similar data types, along with their connection to clinical phenotypes and medical outcomes with an emphasis on patient-specific data and precision medicine applications. We welcome submissions on topics including integration of multiple types of large-scale biological data, personalized risk prediction or intermediate phenotype prediction, mechanistic disease understanding, and advances in deep learning and artificial intelligence for application to precision medicine.
Session Topics
We invite contributions in a wide range of computational topics applicable to precision medicine, both in and outside the clinic. This session will cover original research and methodologies addressing precision medicine's most pressing current and anticipated challenges related to human health.
Examples of topics within the scope of this session include but are not limited to:
• Exploration of novel machine learning and deep learning approaches for the integration, interpretation, and application of genome variation data and other large-scale biological data.
• Methods that use and integrate genomic, proteomic, transcriptomic, metabolomic, metagenomic, and other -omics data for high-resolution individualized health-related outcomes.
• Analysis of large-scale patient-specific biological data to predict clinical phenotypes.
• Development of causal or predictive models for relating genotype, gene expression, disease labels and intermediate phenotypes, as well as multi-omics models that incorporate intermediate phenotypes in evaluating disease status.
• Large language models contributing to novel insight into genomic variation or impact on pathogenesis and pharmacogenetics.
• Methods or approaches to clinically annotate and interpret whole-genome sequencing data or long-read sequencing data.
• Methods for making use of rare and low frequency noncoding variants arising from whole-genome sequencing, or structural variants and epigenetic variation arising from long-read sequencing.
• Innovations in polygenic risk score estimation and their clinical applications.
• Methods for multi-ethnic analyses that explain observed health disparities, and approaches to ensure equity and effectiveness of precision medicine for populations from diverse genetic and environmental backgrounds.
• Methods for estimating and/or incorporating genetic ancestry for genomic discovery or precision medicine implementation.
• Methods or approaches for interpreting genome relationship with the microbiome in the clinical context.
• Methods for analyzing, interpreting, and applying pharmacogenetics information.
• Methods that enable data and model sharing while preserving patient privacy.
• Methods for incorporating data from biological perturbations generated by advanced genome editing techniques into phenotype predictive or integrative models.
Session Organizers
Nilah M. Ioannidis, University of California, Berkeley; nilah@berkeley.edu
Tayo Obafemi-Ajayi, Missouri State University; TayoObafemiAjayi@missouristate.edu
Anne O’Donnell-Luria, Broad Institute; odonnell@broadinstitute.org
Steven E. Brenner, University of California, Berkeley; brenner@compbio.berkeley.edu
Submission Information
The submitted papers are fully reviewed and accepted on a competitive basis.
Important Dates (no extensions): (https://psb.stanford.edu/keydates)
Paper Format and Submissions:
Please see the PSB paper format template and instructions at https://psb.stanford.edu/psb-online/psb-submit.
Unlike the abstracts at most biology conferences, papers in the PSB proceedings are archival, rigorously peer-reviewed publications. PSB publications are Open Access and linked directly from MEDLINE/PubMed and Google Scholar for wide accessibility. They should be thought of as short journal articles that may be cited on CVs and grant reports.
Travel Fellowships for Trainees:
PSB traditionally provides fellowships for select trainees. The application process opens upon paper acceptance.
Poster Format:
Poster presenters will be provided with an easel and a poster board 32"W x 40"H (80x100cm). One poster from each paid participant is permitted. See the submission portal web site for the instructions regarding poster submissions.